Hello,
I’m using a pre-trained VGG to extract features at certain layer to avoid the dreaded OOM. The forward pass seems to be fine but during the backward pass, I got the error:
RuntimeError: set_sizes_and_strides is not allowed on a Tensor created from .data or .detach().
If your intent is to change the metadata of a Tensor (such as sizes / strides / storage / storage_offset)
without autograd tracking the change, remove the .data / .detach() call and wrap the change in a `with torch.no_grad():` block.
For example, change:
x.data.set_(y)
to:
with torch.no_grad():
x.set_(y)
When I test the same code using on my local machine with a cpu, this error does not happen. I’m not sure how to tackle this. Any thought is much appreciated 
Full stack here:
loss.backward()
File "/opt/conda/lib/python3.8/site-packages/torch/_tensor.py", line 264, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs)
File "/opt/conda/lib/python3.8/site-packages/torch/autograd/__init__.py", line 153, in backward
Variable._execution_engine.run_backward(
File "/opt/conda/lib/python3.8/site-packages/torch/autograd/function.py", line 87, in apply
return self._forward_cls.backward(self, *args) # type: ignore[attr-defined]
File "/opt/conda/lib/python3.8/site-packages/torch/utils/checkpoint.py", line 122, in backward
outputs = ctx.run_function(*detached_inputs)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1056, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/container.py", line 139, in forward
input = module(input)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1056, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 446, in forward
return self._conv_forward(input, self.weight, self.bias)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 442, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: set_sizes_and_strides is not allowed on a Tensor created from .data or .detach().
If your intent is to change the metadata of a Tensor (such as sizes / strides / storage / storage_offset)
without autograd tracking the change, remove the .data / .detach() call and wrap the change in a `with torch.no_grad():` block.
For example, change:
x.data.set_(y)
to:
with torch.no_grad():
x.set_(y)